Dynamic and Robust Capacitated Facility Location in Time Varying Demand Environments

This dissertation studies models for locating facilities in time varying demandenvironments. We describe the characteristics of the time varying demand that motivatethe analysis of our location models in terms of total demand and the changein value and location of the demand of each customer. The first part of the dissertationis devoted to the dynamic location model, which determines the optimaltime and location for establishing capacitated facilities when demand and cost parametersare time varying. This model minimizes the total cost over a discrete andfinite time horizon for establishing, operating, and closing facilities, including thetransportation costs for shipping demand from facilities to customers. The modelis solved using Lagrangian relaxation and Benders? decomposition. Computationalresults from different time varying total demand structures demonstrate, empirically,the performance of these solution methods.The second part of the dissertation studies two location models where relocationof facilities is not allowed and the objective is to determine the optimal locationof capacitated facilities that will have a good performance when demand and costparameters are time varying. The first model minimizes the total cost for openingand operating facilities and the associated transportation costs when demand andcost parameters are time varying. The model is solved using Benders? decomposition. We show that in the presence of high relocation costs of facilities (opening and closingcosts), this model can be solved as a special case by the dynamic location model. Thesecond model minimizes the maximum regret or opportunity loss between a robustconfiguration of facilities and the optimal configuration for each time period. Weimplement local search and simulated annealing metaheuristics to efficiently obtainnear optimal solutions for this model.